# statsmodels.tsa.stattools.pacf_burg¶

statsmodels.tsa.stattools.pacf_burg(x, nlags=None, demean=True)[source]

Burg’s partial autocorrelation estimator

Parameters
xarray-like

Observations of time series for which pacf is calculated

nlagsint, optional

Number of lags to compute the partial autocorrelations. If omitted, uses the smaller of 10(log10(nobs)) or nobs - 1

demeanbool, optional
Returns
pacfndarray

Partial autocorrelations for lags 0, 1, …, nlag

sigma2ndarray

Residual variance estimates where the value in position m is the residual variance in an AR model that includes m lags

References

*

Brockwell, P.J. and Davis, R.A., 2016. Introduction to time series and forecasting. Springer.